Rapid measurement of formed blood component sedimentation rate from small sample volumes

ABSTRACT

Devices and methods are described for measuring formed blood component sedimentation rate. Some of the methods may use (1) centrifugal techniques for separating red blood cells from plasma and (2) video and/or still imaging capability. Both may be used alone or in combination to accelerate formed blood component sedimentation and to measure its rate. In one example, the method may advantageously enable rapid measurement of sedimentation rate using small blood sample volumes. Automated image analysis can be used to determine both sedimentation rate and hematocrit. Automated techniques may be used to compensate for effects of hematocrit on uncorrected sedimentation rate data.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Application Ser.No. 61/673,037 entitled “Rapid Measurement of Formed Blood ComponentSedimentation Rate from Small Sample Volumes” filed Jul. 18, 2012.

BACKGROUND

Erythrocyte sedimentation rate (ESR), also called a sedimentation rateor Biernacki Reaction, is the rate at which red blood cells sediment,typically measured over a period of one (1) hour. It is a commonhematology test and is a non-specific measure of inflammation. Toperform the test using a traditional technique, anti-coagulated blood isplaced in an upright tube, known as a Westergren-Katz tube, and the rateat which the red blood cells sediment is measured and reported inmm/hour. Specifically, the Westergren method requires collecting 2 ml ofvenous blood into a tube containing 0.5 ml of sodium citrate. The sampleshould be stored no longer than 2 hours at room temperature or 6 hoursat 4° C. The blood is drawn into the Westergren-Katz tube to the 200 mmmark. The tube is placed in a rack in a strictly vertical position forone hour at room temperature, at which time the distance from the lowestpoint of the surface meniscus to the interface between red-cell freeplasma and the portion of the sample occupied by red-cells measured. Thedistance moved by the erythrocyte interface, expressed as millimeters in1 hour (mm/h) is the ESR.

The ESR is governed by the balance between pro-sedimentation factors,mainly fibrinogen (but possibly also the levels of serum C-reactiveprotein (CRP), immunoglobulins A and G, alpha(1)-acid-glycoprotein andalpha(1)-antitrypsin), and sedimentation resisting factors, mainly thenegative charge of the erythrocytes (zeta potential). In one example ofthe effects of inflammation, high concentrations of fibrinogen in bloodplasma causes red blood cells to adhere to each other. The red bloodcells adhere to form stacks called ‘rouleaux,’ which settle faster thanindividual red cells. Rouleaux formation can also occur in associationwith some lymphoproliferative disorders in which one or moreimmunoglobulins are found in high concentrations. Rouleaux formationcan, however, be a normal physiological finding in horses, cats, andpigs.

ESR is increased by any cause or focus of inflammation. ESR is increasedin pregnancy and rheumatoid arthritis, and decreased in polycythemia,sickle cell anemia, hereditary spherocytosis, and congestive heartfailure. The basal ESR is slightly higher in females.

The standard predicate method for measuring ESR is the Westergren test,and the test uses a large volume of blood, typically several ml. Ittypically requires one hour incubation since many samples have ESRs aslow as 10 mm/hour. Inflammatory factors which increase ESR includefibrinogen, C-Reactive Protein (CRP) and some immunoglobulins, which canincrease ESR to as high as 100 mm/hour.

Traditional techniques of performing sedimentation tests have variouslimitations. For instance as discussed, Westergren sedimentation testsrequire a substantially high volume of blood to be withdrawn.Additionally, traditional sedimentation test techniques take asubstantial period of time and may result in time lags in obtaining testresults that could lead to delays in diagnoses and treatments which canhave a deleterious effect on a patient's health.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

SUMMARY

It may be desirable to have sedimentation rate test that can becompleted in a very short time, such as but not limited to being on theorder of seconds to a few minutes. For distributed test settings, it mayalso be desirable to have sedimentation rate measurements that use onlysmall blood volumes, such as can be obtained by alternate site,non-venous blood draws or minimal venous draws. It may be furtherdesirable to make the sedimentation measurement in an automated fashion(no human observation required) and to create an objective record of themeasurement. Additionally, further information useful in optimizingmanagement of patients may be obtained by performing and/or maximizingthe speed of multiplexed measurement of other analytical parameters inparallel with sedimentation rate measurement.

In one embodiment described herein, the sedimentation rate measurementmethod may use (1) centrifugal techniques for separating red blood cellsfrom plasma and (2) video and/or still imaging capability. Both may beused alone or in combination to accelerate erythrocyte sedimentation andto measure its rate. Of course, techniques other than centrifugation foraccelerating sedimentation may be used in place of or in combinationwith centrifugation to separate blood components.

In one non-limiting example, the method may advantageously enable (1)rapid measurement of ESR (seconds) with small blood sample volumes suchas about 20-25 microliters (“uL” or “μL”) or less, (2) use of automatedimage analysis to determine both red blood cell sedimentation rate andhematocrit, and/or (3) automated techniques to compensate for effects ofhematocrit on uncorrected ESR so as to provide a value corresponding tothe traditional Westergren method. Of course, alternative embodimentsusing large volumes of blood are not excluded. Because of the ability tocorrect for hematocrit, some embodiments of sedimentation measurementtechniques described herein is more robust than traditional Westergrentechniques and can be used on sample with fibrinogen and/or hematocritlevels outside the narrow range required by Westergren testing.

Using an embodiment herein, corrected ESR can be acquired in a matter ofseconds using a small blood volume and which compensates for effects ofhematocrit ESR. The results acquired in a matter of seconds duringinitial centrifugation can accelerate deliver of a diagnosis to thepatient.

Moreover, in the context of multiplexed assay procedures, a commonpre-processing step already involves separating red and white cells fromplasma or serum prior to measurements of cellular markers and ofanalytes present in plasma/serum. Thus, it is convenient to incorporatean ESR measurement along with such a pre-processing procedure that willalready be performed during the course of assay preparation. The ESRmeasurement will not create significant burden in terms of additionalprocessing time or use of limited quantities of blood available fromnon-venous collection methods. By way of non-limiting example, it shouldbe understood that assay processing, including pre-processing step(s),may occur in a single instrumented system. Optionally, some embodimentsmay perform one or more steps in one instrument and another one or moresteps in another instrument.

It should also be understood that embodiments described herein may beadapted to have one or more of the features described below. In onenon-limiting example, a typical protocol may take 20 uL of blood in acentrifuge vessel and spin in a swing-out centrifuge rotor at 4000 rpm(580 *g) for about 10 s. During this time, the interface between theportion of the sample containing the red blood cells and that cleared ofred blood cells is observed by video imaging. Although other timeperiods are not excluded, it can be advantageous to obtain the ESRmeasurement in this short period of time. Optionally, some embodimentsmay correct these “raw” ESR values for the effects of hematocrit.Hematocrit may be measured in the same operation as that used formeasurement of raw ESR. In one non-limiting example, following arelatively low speed spin during centrifugation to measure ESR, the spinspeed is increased to pack the red blood cells. Hematocrit is determinedby image analysis of the packed red blood cells and the supernatantplasma volumes. Optionally, other techniques for measuring hematocritmay also be used to correct “raw” ESR values.

At least some of the embodiments herein may have ESR corrected withoutusing calculations of the slope of an essentially linear transform ofthe non-linear (exponential) portion of the sedimentation curve.

At least some of the embodiments herein may have ESR corrected withoutcalculating a mathematical function for a plurality of theerythrocyte/plasma interface positions occurring in a non-linear portionof the sedimentation curve.

At least some of the embodiments herein may have ESR corrected withoutselecting a segment of the sedimentation curve which lies in saidnon-linear portion of the sedimentation curve.

At least some of the embodiments herein may have ESR corrected basedonly on measurements of linear portion(s) of the sedimentation curve.

At least some of the embodiments herein may have ESR corrected based onmeasurements which consists essentially of linear portion(s) of thesedimentation curve. By “consists essentially of”, we mean at least 90%or more of the measurement is based on the linear portion(s).

At least some of the embodiments herein may have ESR corrected withoutdetermining a mathematical function for a non-linear segment of thesedimentation curve representative of the magnitude of intercellularerythrocyte repulsion in the blood sample.

At least some of the embodiments herein may have ESR corrected withoutnegating the time period during the centrifugation of the sample duringwhich a linear portion of the sedimentation curve is formed.

At least some of the embodiments herein may have ESR corrected forhematocrit using hematocrit measurements not derived from centrifugaltechniques, such as for example, lysis of red cells with detergent andmixing with ferricyanide and cyanide followed by measurement of theabsorbance of the cyan-met-hemoglobin formed.

At least some of the embodiments herein may have the blood sampleadjusted so that it is at a known hematocrit level for the sedimentationmeasurement.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a graph of red cell sedimentation of high, medium, and lowESR blood samples in Westergen-Katz tubes.

FIGS. 2A-2B are images of blood samples in transparent centrifugationvessels.

FIG. 3 shows a schematic of a centrifuge with one embodiment of adetection system.

FIGS. 4-5 show images captured using one embodiment of a detectionsystem.

FIGS. 6A-7C show a series of corrected and uncorrected images ofinterfaces in a blood sample undergoing centrifugation.

FIGS. 8A-8B show various kymographs for one test sample.

FIG. 9 shows a sedimentation graph for one test sample

FIGS. 10A-10B show sedimentation graphs with various fitted functionsfitted to the data of FIG. 9 plotted thereon.

FIGS. 11-14 are graphs showing various sample sedimentationcharacteristics for samples with various levels of added fibrinogen.

FIG. 15 shows sedimentation rates for several blood samples manipulatedto have different hematocrit levels.

FIG. 16 is a graph of interface positions over time for the samples withdifferent hematocrit levels also shown in FIG. 15.

FIG. 17 is a graph of interface positions over a 10 second period oftime for one sample with different hematocrit levels.

FIG. 18A shows an ESR graph of one embodiment herein without hematocritcorrection.

FIG. 18B shows an ESR graph of one embodiment herein with hematocritcorrection.

FIG. 18C shows a graph of hematocrit measurement based on hemoglobinconcentration according to one embodiment herein.

FIGS. 19 and 20 illustrate sedimentation rates for several samples (asspecified in FIG. 15) plotted using non-LOG and LOG axis.

FIG. 21 shows a kymograph illustrating a white blood cell interface.

FIG. 22 shows a schematic of one embodiment of an integrated systemhaving sample handling, pre-processing, and analysis components.

DETAILED DESCRIPTION

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive of the invention, as claimed. It may be notedthat, as used in the specification and the appended claims, the singularforms “a”, “an” and “the” include plural referents unless the contextclearly dictates otherwise. Thus, for example, reference to “a material”may include mixtures of materials, reference to “a compound” may includemultiple compounds, and the like. References cited herein are herebyincorporated by reference in their entirety, except to the extent thatthey conflict with teachings explicitly set forth in this specification.

In this specification and in the claims which follow, reference will bemade to a number of terms which shall be defined to have the followingmeanings:

“Optional” or “optionally” means that the subsequently describedcircumstance may or may not occur, so that the description includesinstances where the circumstance occurs and instances where it does not.For example, if a device optionally contains a feature for a samplecollection well, this means that the sample collection well may or maynot be present, and, thus, the description includes both structureswherein a device possesses the sample collection well and structureswherein sample collection well is not present.

Referring now to FIG. 1, the kinetics of erythrocyte/plasma interfacefor a set of blood samples is shown. FIG. 1 shows the kinetics oferythrocyte sedimentation in Westergren-Katz tubes for a range ofsamples with the continuous line showing High ESR, the dashed lineshowing Medium ESR, and the dots showing Low ESR. Despite the reportingof the Westergren ESR as a single number (mm/hour) as seen in FIG. 1,the rate of sedimentation varies dramatically during the hour, beginningslowly, increasing, and then decreasing. The standard Westergren methodrecords ESR at a single position at one hour, to give the meansedimentation rate over that hour. A more recent method, called theSigma ESR has shown better correlation with clinically relevantvariables by taking the sum of the distance moved at 20, 30, 40, 50 and60 minutes.

Sedimentation Curve Measurement

A variety of techniques may be used to establish a sedimentation ratecurve for one or more formed blood components. Although the presentapplication is described mostly in the context of measuring erythrocytesedimentation rate, systems and methods herein can also be adapted foruse in measuring sedimentation rates for other formed blood componentssuch as but not limited to white blood cells, platelets, or the like.

In one nonlimiting example, one technique described herein comprisestaking images at several time points during sedimentation by placing thesample vessel in a centrifuge, spinning for a few seconds, stopping thespin, removing the vessel, placing it in a viewer, taking an image, andrepeating the above to obtain multiple images over time. From a devicesimplicity standpoint, it is helpful in that it simplifies hardwareimplementation for obtaining such images. The ability to measuresedimentation is discussed elsewhere herein where the slope from theinitial (linear) part of the sedimentation curve is used to calculatethe ESR.

It should be understood of course, that some embodiments may obtain suchimages/data regarding interface position while the container is in-situin the centrifuge and without having to stop the centrifuge to removethe sample vessel for imaging. The in-situ images may be taken while thecentrifuge rotor is in motion or at rest. It should also be understoodthat although discrete images may be taken, videos, continuous imaging,and multi-frame per second imaging may also be used.

Referring now to FIGS. 2A and 2B, examples of erythrocyte interface areshown before centrifugation and at an early stage of centrifugation. Byway of non-limiting example, the centrifuge vessel may be made in wholeor in part of transparent material such as transparent plastic(injection-molded polystyrene). In some embodiments, the transparentportions may be windows, clear ports, or clear strips in the vesselaligned to allow for imaging of the desired blood component interface ofsample in the vessel. In the present embodiment, the radius of thecentrifuge vessel at its mid-point is 35 mm (radial distance from theaxis of rotation). In one embodiment, outer radius is 35 mm, inner (i.e.to top surface of liquid) is 28 mm, therefore midpoint is 31.5 mm. Thesample length in the vessel is 7 mm and the vessel inner diameter is 2.3mm. Changes in the sample vessel geometry or volume of sample to betested can be accounted for by re-calibrating the empirical parametersused for hematocrit correction factor as will be discussed elsewhereherein.

Other suitable centrifuge designs and features including dimensions forthe centrifuge vessels, construction of the centrifuge rotor, andcentrifuge size are disclosed in co-pending U.S. patent applicationsSer. Nos. 13/355,458 and 13/244,947, all fully incorporated herein byreference for all purposes. Other components of the present systemincluding suitable imaging devices and fluid handling systems are alsodescribed in the applications incorporated by reference. For example,the ability of digital cameras such as those described in thoseapplications may be used to measure very small distances and rates ofchange of distances to measure ESR. Image analysis can be used tomeasure the movement of the interface between red cells and plasma.

By way of nonlimiting example, in some embodiments, only twomeasurements taken at early times (seconds) after centrifugation hasbegun is sufficient to define the sedimentation rate with highprecision. In one embodiment, some may take the first image after aninitial minimum centrifuge speed is reached and then a second image maybe taken about 10 seconds later. Of course, other time periods for theimages are not excluded so long as they are in the linear portion of thesedimentation curve.

Viewing FIGS. 2A and 2B, erythrocyte interface position in a stationary(vertical) tube (short time of centrifugation) can be seen. In thepresent nonlimiting example, the swinging centrifugation vessel isstopped and oriented vertically in the FIGS. 2A and 2B. Of course,stationary imaging does not need tube to be vertical (so long as it isdone quickly) since surface tension holds interface in place. Typically,this is done within a second or two else RBC interface will begin toflow.

As seen in FIGS. 2A and 2B, there is a clearly visible sharp transitionbetween part of the sample occupied by red blood cells and plasma. Thehorizontal erythrocyte interface level is clearly visible in theseimages. The distance moved by the interface in FIG. 2B relative to FIG.2A corresponds to a large number of pixels (50/mm) in the images. Thus,as seen, the number of pixels traveled by the interface allows foraccurate tracking of the change in interface position. Of course, otherimage resolutions such as but not limited 50 pixels/mm to 1000 pixels/mm(or higher) can be used to provide even greater granularity in terms ofnumbers of pixels per mm or other unit length. Others may use fewerpixels per unit length so long as the resolution is sufficient toaccurately determine the change in interface position. Some embodimentsmay magnify the image so that more pixels are associated with theinterface and thus more pixels are associated with change in position ofthe interface. Some may use detectors with greater numbers of pixels perunit area. This increases the sensitivity of the measurement bymeasuring more pixels and having the ability to detect even more subtlechanges in interface position.

In one embodiment, a method is provided which uses a transparent windowin the centrifuge housing so that a video record of sedimentation can bemade during the low-speed centrifugation. Moreover, the centrifugalfield causes the meniscus to become straighter (at right angles to thecentrifugal force vector) making measurement of small settling distanceseasier. This may be particularly true when images are captured while thecentrifuge rotor is spinning By spinning a small volume (20-25 uL) ofblood at intermediate speeds (typically 4000 rpm, although 2000 to 6000rpm may also suitable), almost complete sedimentation of red blood cellsis achieved in this embodiment within about three minutes. In practice,one method may take sedimentation measurements for a few seconds atrelatively low speed (4000 rpm) then the speed would be increased toabout 10,000 rpm for about three minutes to pack the red blood cells anddetermine the hematocrit. This multi-stage spinning at differentcentrifugation speeds allows for imaging for sedimentation and thenrapid spin down to achieve compaction of blood components and separationfrom blood plasma.

Referring now to FIG. 3, one embodiment of a centrifuge 100 capable ofmonitoring interface position will now be described. To monitorsedimentation, an image capture device 110 may located near thecentrifuge 100, with a light source 112 such as but not limited to agreen, LED positioned to provide illumination from an opposing location.The image capture device 110 may be a still camera, a high speed camera,a video camera, or other device sufficient to detect the location of theinterface. Of course, other detectors such as but not limited tonon-image capture devices are also not excluded. By way of non-limitingexample, one non-visual imaging device here may be a photodiode whichcan function as a detector to detect when a blood component interfacepasses the detector, or by bulk transmission of light to detectproportion of volume blocked by RBCs or other blood component(s).Non-visual imaging detectors can be used even if they may not actuallyconvey a visual image but can still detect interface level positionand/or position change in the sample.

Any descriptions of cameras, or other detection devices describedelsewhere herein may apply. In one example, the image capture device 110may be a digital camera. Image capture devices may also include chargecoupled devices (CCDs) or photomultipliers and phototubes, orphotodetector or other detection device such as a scanning microscope,whether back-lit or forward-lit. In some instances, cameras may useCCDs, CMOS, may be lensless (computational) cameras (e.g.,Frankencamera), open-source cameras, or may use any other visualdetection technology known or later developed in the art. Cameras mayinclude one or more feature that may focus the camera during use, or maycapture images that can be later focused. In some embodiments, imagingdevices may employ 2-d imaging, 3-d imaging, and/or 4-d imaging(incorporating changes over time). Imaging devices may capture staticimages. The static images may be captured at one or more point in time.The imaging devices may also capture video and/or dynamic images. Thevideo images may be captured continuously over one or more periods oftime. Any other description of imaging devices and/or detection unitsmay also be applied, preferably so long as they are able to detectchanges in interface position.

In one non-limiting example, a light source 112 may be a light-emittingdiode (LED) (e.g., gallium arsenide (GaAs) LED, aluminum galliumarsenide (AlGaAs) LED, gallium arsenide phosphide (GaAsP) LED, aluminumgallium indium phosphide (AlGaInP) LED, gallium(III) phosphide (GaP)LED, indium gallium nitride (InGaN)/gallium(III) nitride (GaN) LED, oraluminum gallium phosphide (AlGaP) LED). In another example, a lightsource can be a laser, for example a vertical cavity surface emittinglaser (VCSEL) or other suitable light emitter such as anIndium-Gallium-Aluminum-Phosphide (InGaAIP) laser, a Gallium-ArsenicPhosphide/Gallium Phosphide (GaAsP/GaP) laser, or aGallium-Aluminum-Arsenide/Gallium-Aluminum-Arsenide (GaAIAs/GaAs) laser.Other examples of light sources may include but are not limited toelectron stimulated light sources (e.g., Cathodoluminescence, ElectronStimulated Luminescence (ESL light bulbs), Cathode ray tube (CRTmonitor), Nixie tube), incandescent light sources (e.g., Carbon buttonlamp, Conventional incandescent light bulbs, Halogen lamps, Globar,Nernst lamp), electroluminescent (EL) light sources (e.g.,Light-emitting diodes-Organic light-emitting diodes, Polymerlight-emitting diodes, Solid-state lighting, LED lamp,Electroluminescent sheets Electroluminescent wires), gas discharge lightsources (e.g., Fluorescent lamps, Inductive lighting, Hollow cathodelamp, Neon and argon lamps, Plasma lamps, Xenon flash lamps), orhigh-intensity discharge light sources (e.g., Carbon arc lamps, Ceramicdischarge metal halide lamps, Hydrargyrum medium-arc iodide lamps,Mercury-vapor lamps, Metal halide lamps, Sodium vapor lamps, Xenon arclamps). Alternatively, a light source may be a bioluminescent,chemiluminescent, phosphorescent, or fluorescent light source.

As seen in FIG. 3, a centrifuge vessel 114 containing a blood sampletherein may be positioned so as to be between the image capture device110 and the light source 112 to enable the position of the formed bloodcomponent interface(s) in the vessel to be visualized. The centrifugerotor 116 may be configured to have an opening, a window, or other areathat allows the centrifuge vessel 114 to be visualized duringcentrifugation. Measuring sedimentation during centrifugation spin maybe used, but it should be understood that measuring sedimentationbetween spins or after spins when the centrifuge is at rest is also notexcluded.

In the present embodiment of FIG. 3, the axis of rotation of thecentrifuge rotor 116 may be vertical. It should be understood that otheraxis of rotation such as horizontal or angled axis of rotation are notexcluded. Some embodiments may have a first orientation during one timeperiod and a different orientation during a second or other time period.

In one nonlimiting example, the positions of the top and/or bottom ofthe centrifuge vessel are obtained by imaging as reference points, andlater these are used to calibrate the liquid and interface levels. FIG.4 shows a camera view of a centrifuge vessel 114 in the centrifuge.Illumination from light source 112 from behind the centrifuge vessel 114allows for visualization of blood sample S and the blood/air interface120. The direction of rotation is shown by arrow 122.

Referring now to FIG. 5, an enlarged view of the interface(s) of theblood sample in the centrifuge vessel 114 will now be described. FIG. 5is an image of sedimenting red blood cells during centrifugation.Air/plasma interface 130 and plasma/red blood cell interface 132 areclearly discernable as sharp lines (separating spatial regions ofdifferent contrast) in the image. Space 134 above the air/plasmainterface, plasma 136, and light 138 blocked red blood cells are alsoshown in the image of FIG. 5.

It should be understood that strobe illumination or capture framessynchronized to the rotor position are not excluded, but in the presentembodiment, are not required for image capture. In this nonlimitingexample for the image of FIG. 5, a 200 ms exposure (short relative tospin times) for the CCD camera image acquisition makes the interfaces130 and 132 clearly visible during the spin (see FIG. 5). This was longcompared to the rotation period (i.e. that many rotations occur duringthe time, so that images blur out). The image blurs around the rotoraxis so that the air/plasma interface and plasma/erythrocyte interfaceare visible as arcs (though there are maybe strobe effects that may alsobe taken into account). Although the data acquisition does not requireframe capture to be synchronized to rotation, some embodiment may usesynchronization. Optionally, some embodiments without synchronizationmay cause striping, which can be compensated for by a combination oflonger exposures and image processing. Other embodiments may use fasterimage acquisition techniques to generate images that minimize and/oreliminate blurring. Some embodiments may use strobe illumination orother techniques to capture images of fast moving objects such as thesample containing vessel during centrifugation.

As seen in FIG. 5, light transmitted through two regions of thecentrifuge vessel 114 may include the air 134 above the liquid, and theplasma between the air/plasma and plasma/erythrocyte interfaces 130 and132 as labeled. The air/plasma interface 130 itself is visible as anarc. Essentially no light makes it through the vessel 114 where theerythrocytes are (although it should be understood that this region isnot completely dark because of the light transmitted when the vessel 114rotates out of the blocking position).

In one embodiment, images are captured for three minutes at five framesper second, with long exposure (˜200 ms), then processed to extract thesedimentation curve. Optionally, the rate of imaging includes but is notlimited to 1, 2, 4, 8, 16, 32, 64, or 128 images per second. Optionally,exposure time includes but is not limited to 10, 20, 40, 80, 160, 320,or 640 ms. Temperature during measurement may also be varied. Althoughmany embodiments herein had measurements performed at room temperature,but other temperatures e.g. 37 C are not excluded. Effect of temperaturewould be taken into account in the calibration, such as for determiningempirical parameters of the correction factor. Also, time to centrifugespin up was typically about 3 seconds, but faster or slower spin uptimes are not excluded.

By way of nonlimiting example, the sedimentation rate of the desiredformed blood component being measured may be defined by:

-   -   1) fitting the plasma/red blood cell interface position versus        time to an exponential, or    -   2) taking the (linear) rate of interface movement over the first        few seconds to give a parameter, which can then be correlated        with Westergren ESR.

Although others settings are not excluded, it should be understood thattimes of sedimentation are usually defined as starting following therotor 116 reaching its target speed when the buckets holding thecentrifuge vessels 114 are oriented radially in the spin plane and soare in optimal position for image capture and processing.

Data Pre-Processing

Image Transformation

Referring now to FIGS. 6A-6B, one embodiment herein may use an imagepre-processing step prior to analysis which may be a combination of (1)conversion of the interface arc to a flat interface and (2) rotation ofthe image to compensate for any minor offsets in the radial direction.This brings off-center pixels in line with the central axis in a waythat has negligible effect on the y positions of the interfaces so thatthe blurred-out arcs from the rotating tube are now horizontal stripes.

As seen in in FIGS. 6A-6B, an initial image transform may be used tocompensate for arcs. The image in FIG. 6B shows a rectangle 150 with theselected area of interest across which the horizontal averaging isperformed, and two short horizontal lines showing where the algorithmhas identified the position of the air/plasma interface 130 and theplasma/erythrocyte interface 132.

This image transformation is desirable to remove the effects of thevertical lines seen in FIG. 6A, caused by a strobe effect between thefrequency of rotation of the centrifuge and the acquisition frequency ofthe camera. A thin vertical (i.e. radial) section measurement would bevulnerable to these lines, which move slowly across the image, but thestraightening transform allows averaging in the x-direction (at rightangles to the radial) and makes the profile immune to the effects of themoving lines. This procedure also improves the signal to noise ratio.

Referring now to FIGS. 7A-7C, examples showing different degrees of arccompensation are shown. Selection of image transformation parameters canbe chosen to introduce a desired level of correction. FIG. 7A showscompensation that is too little. FIG. 7B shows compensation that is justright. FIG. 7C shows too much arc compensation.

For each dataset using a script that produces a series of images withdifferent arc and rotation angle correction, superimposing a series ofhorizontal lines 160 on the images allows for judgment of when theinterfaces are flat (horizontal in the images of FIGS. 7A-7C). Thisjudgment of appropriate degree of arc correction can be determined by aprogrammable processor configure for image processing, pre-set based ona calibration procedure, or may be selected based on human review.

Once these parameters are selected, the acquired image information,which may be a video, is put through the transformation. A region ofinterest may be chosen that covers both the whole range of positions forboth the air/plasma interface 130 and the erythrocyte interface 132.Optionally, some embodiments may choose a region of interest coveringonly one of the interfaces 130 or 132. Optionally, some embodiments maybe configured to target one or more other areas of interest in thesample.

Sedimentation Curve Extraction

Referring now to FIGS. 8A-8B, for each timepoint in the plurality ofimages, one embodiment of the technique herein averages the pixelintensity values for each row (across the vessel 114) within the regionof interest 150 to produce a single column representing the intensityradially down the vessel. The columns for each timepoint are thenassembled into a kymograph, i.e. an image where the x-axis representstime and the y axis represents radial position along the tube.

FIG. 8A shows a kymograph according to one embodiment described herein.The kymograph of FIG. 8A shows average image intensity down the tube(y-axis) over time (x-axis). FIG. 8A shows an air interface 130, plasma136, plasma/red blood cell interface 132, and red blood cells 140. Morespecifically, the dark horizontal line near the top of the imagerepresents the air/plasma interface 130, the bright area below itrepresents the light transmitted through the plasma 136, and the darkarea at the bottom is where the light is blocked by the red blood cells140.

FIG. 8B shows that, to extract the position of the air/plasma interfaceand the plasma/erythrocyte interface, a first derivative (edgedetection) of the interface with respect to time may be determined.Derivative is with respect to distance down the tube (y-axis) and nottime (x-axis). FIG. 8B shows the positions of the air/plasma (upper)interface 130 and plasma/erythrocyte (lower) interface 132.

In one nonlimiting example, the positions of the two local maxima of theimage in FIG. 8B, one representing the air/plasma interface and otherthe plasma/erythrocyte interface are determined. To convert these(pixel) positions into volume occupied by the whole sample and volumeoccupied by red blood cells, the y-position of the top and bottom of thecentrifuge tube (such as recorded from the stationary tube image shownin FIG. 2) are used as reference locations together with knowledge ofthe shape of the centrifuge vessel.

As seen in FIG. 9, the plasma/erythrocyte interface position isconverted to the volume fraction occupied by red blood cells and plottedagainst time as a centrifuge-assisted sedimentation curve 180. Thiscurve in FIG. 9 is the result of one nonlimiting example of acentrifuge-based method of determining a sedimentation curve extractedfrom a video record.

Calculating ESR From Sedimentation Curve

Once the sedimentation curve of FIG. 9 is obtained for each sample,there are many possible ways to extract parameters that correlate withESR. One simple way to reduce the curve to a single parameter foranalysis is to fit a single exponential to the curve of theplasma/erythrocyte interface using standard nonlinear least squaresfitting.

One such example is shown in FIG. 10A. For FIG. 10A, data in the graphis shown as black dots 200, the x-axis is time in seconds, and they-axis is the volume fraction occupied by red blood cells. A singleexponential fit is shown as line 202.

Referring now to FIG. 10B, data in the graph is shown as black dots 200.FIG. 10B shows a substantially bi-linear fit. The gradient of theinitial linear portion shown by linear fit 210 may be determined, aswell as the time 212 of the transition between the initial linearsection, and the non-linear region where packing slows, shown here bythe red line 214.

Although these simple techniques of using standard nonlinear leastsquares fitting may yield some information related to ESR, whencomparing such measurements with traditional Westergren ESRmeasurements, the correlation based on the nonlinear least squares (NLS)fitting leaves room for improvement as NLS by itself does not take intoaccount certain correction factors.

Plasma Protein Impact on ESR

To extract ESR parameters that more closely correlate with traditionalWestergren ESR measurements, it is helpful to understand some factorswhich may impact ESR measurements. The parameter of interest (ESR)responds to the concentration of certain plasma proteins and can bedirectly affected/manipulated by adding one of these proteins, (e.g.,fibrinogen) to the blood sample.

In the present example, as a technique to provide samples with a widerange of ESR values, exogenous fibrinogen was used to create bloodsamples with ESR values spanning the whole range of interest (0-120 mm/hin the Westergren method). FIG. 11 shows how adding fibrinogen increasesthe Westergren ESR values.

As seen in FIGS. 11 to 14, several parameters from centrifugal analysisshow a good correlation with fibrinogen levels (and therefore with ESR),most notably the time constant from a single exponential fit, the timeto onset of packing, and the initial linear gradient. Referring to FIGS.12, 13, and 14, in some embodiments, each of these parameters can beused to obtain an estimate of the Westergren ESR value. The singleexponential-fit time constant and the packing onset time both have theadvantage of being independent of y-scale. The packing onset time andthe initial linear gradient have the advantage of having clear physicalmeanings.

FIG. 11 shows that Westergren ESR values increase with increasing addedFibrinogen. FIG. 11 illustrates a single sample with different levels offibrinogen added therein.

FIG. 12 shows a time constant from a single exponential fit of the rawsedimentation curve which shows good correlation with added fibrinogenlevels

FIG. 13 shows time to the onset of cell packing which shows goodcorrelation with added fibrinogen levels.

FIG. 14 shows initial linear gradient of the raw sedimentation curveswhich show good correlation with added fibrinogen levels.

Hematocrit Impact on ESR

It should be understood that, in addition to fibrinogen, hematocrit isanother factor that affects Westergren and other ESR measurements. Infact, Westergren erythrocyte sedimentation is strongly affected byhematocrit. In the Westergren method, many laboratories either do notreport results for samples with hematocrits greater than about 45% oradjust the sample hematocrit to a fixed level (usually 45%) beforemeasuring ESR. The present embodiment of the method is actually betterthan the Westergren technique, in that Westergren saturates (i.e. doesnot respond to fibrinogen <10 mg/ml), whereas the present embodiment ofthe method does not saturate out to 15 mg/ml.

Centrifuge-based ESR sedimentation is even more strongly affected byhematocrit levels than measurements under gravity. For at least someembodiments here, the increased dependency on hematocrit is also becauseof the lower volumes—and consequently smaller vessel dimensions.Increasing hematocrit typically means the erythrocytes start closertogether, increasing the viscosity of the blood by presenting physicalbarriers to free movement, and decreasing the maximum distance theinterface can move before the cells become packed, all of which decreasethe ESR, independent of fibrinogen from inflammation.

To illustrate the dramatic confounding effect of hematocrit,centrifuge-based ESR measurements, performed by taking the same sampleof blood and adjusting the hematocrit before measuring the ESR, showthat a person with a typical hematocrit of 45% and a normal ESR of 22mm/h would register as 5 mm/h (very low) if the hematocrit were 60% and93 mm/h (very high) if the hematocrit were 35%, even though there are nochanges in the plasma protein levels which are clinically important. Inother words, variations of ESR due to hematocrit can dominate variationsof ESR due to plasma proteins the clinician is interested in.

There are several traditional approaches to compensating for thisconfounding effect of hematocrit. One approach is using the hematocritcompensation curves, e.g. from Dintenfass (1974). Rather than correctingfor hematocrit using a chart, a more accurate (if more labor-intensive)way to remove the confounding effect is simply to alter the hematocritto a standard value before the test. Some ESR techniques, e.g. the‘hematocrit corrected ESR’ include an initial such step that fixes thehematocrit to a set value e.g. 45%, so that the measured ESR reallyreflects the protein content of the plasma (clinically relevant), ratherthan the hematocrit (Borawski and Myśliwiec 2001).

As seen in FIG. 15, to understand and estimate the effects ofhematocrit, a set of eleven (11) samples were adjusted to 35%, 45% and55% hematocrit, then tested by the centrifuge ESR and Westergren ESRtechniques. Correlations are shown for centrifuge single exponentialtime constant with Westergren ESR for hematocrit adjusted clinical bloodsamples. Samples correlate well within each hematocrit, but samples arenot well correlated across all hematocrits.

Referring now to FIG. 16, the position of plasma/erythrocyte interfaceas a function of time is plotted on the chart for different clinicalsamples with different hematocrit levels for centrifuge-based ESRexperiments. Several blood samples having unadjusted and adjustedfibrinogen levels and hematocrits are shown: red square: 35%, greentriangle, 45% and blue diamond 55% hematocrit. FIG. 16 shows completesedimentation profiles while FIG. 17 shows sedimentation profiles for ashorter period of time (<10 s) for an initial measurement period for onesample adjusted to the given hematocrits. The sedimentation profiles forthe samples show a sharp descent during the initial measurement period,with the interface position falling almost linearly with time duringthat initial measurement period. The sedimentation rate then slows asthe red blood cells pack together. Many data sets corresponding tovarious hematocrits (as indicated) and various ESR rates are shown inFIG. 16.

In FIG. 17 where sedimentation over short initial time periods (<10 s)are shown, the high quality of the data obtained with such shortmeasurement times show a linear sedimentation rate for all hematocritlevels during the initial period. In one embodiment described herein,the linear region of the sedimentation profiles can be used to extract asedimentation velocity. The raw sedimentation velocities are plottedagainst Westergren ESR. Given that the three fit lines corresponding tothe three hematocrit levels in FIG. 17 are discontinuous, compensationfor hematocrit is desirable to derive the clinically significant ESRvalue from the raw value.

As a further example, FIG. 18A shows the logarithm of the erythrocytesedimentation rates extracted from sedimentation profiles uncorrectedfor hematocrit) . FIG. 18A also shows that centrifuge-basedsedimentation rates are strongly dependent on hematocrit, more so thanthe Westergren-based sedimentation rates. The narrow cross-section ofthe centrifuge tube increases hydrodynamic resistance to fluid flow dueto red blood cells. The centrifugation process involves flow of plasmathrough a bed of red blood cells, which offer hydrodynamic resistance.This resistance is a function of the volume fraction of red blood cells,i.e., the hematocrit.

To obtain a better correlation between the centrifuge-based andWestergren sedimentation rates, the centrifuge-based sedimentation rateswere corrected for effect of hematocrit. The correction used can berepresented by,

${U_{corr} = \frac{U_{uncorr}}{\left( {1 - \frac{\varphi}{\varphi_{\max}}} \right)^{\gamma}}},$

where U_(uncorr) and U_(corr) are the uncorrected (raw) and correctedsedimentation rates respectively, φ is the volume fraction of cells(hematocrit), and φ_(max) and γ are empirical parameters obtained bycurve fitting. The correction factor represents a simple mathematicalform to account for the increased drag exerted by red blood cells. Itshould be understood that this functional form was found to be able tocorrect for hematocrit, but other functions would work too.

By way of non-limiting example, one way of calculating φ_(max) and γ isby way of a calibration technique such as but not limited to thefollowing: for a diverse set of samples (different hematocrits, ESRvalues, etc. . . ), the ESR value is determined using a referencemethod, and by the centrifuge-based method. The φ_(max) and γ parametersare determined as a calibration for each centrifuge setup and may changebased at least in part on vessel geometry and volume of sample. Thus, ifat least one of those factors is changed, it may be desirable tore-calculate the parameters. For one centrifuge setup as describedherein, optimal values of these parameters were obtained as:φ_(max)=1.67 and γ=3.85. It should be understood that these parametersare for fit optimization and do not relate directly to physicalparameters.

Hematocrit Measurement Techniques

For purposes of calculating the hematocrit correction factor, it shouldbe understood that the value for hematocrit may be known prior to thestart of the centrifuge-based sedimentation test and in such situations,corrected ESR results can be obtained quickly based on the initiallinear portion of the sedimentation and the known hematocrit level,without having to wait until the erythrocytes have been fully compactedby centrifugation. Optionally, some embodiments may determine hematocritlevels during or after centrifugation.

Hematocrit measurement by non-centrifugal before, during, or aftercentrifugation includes at least the following. One technique involvesmeasurement of hemoglobin concentration. For example, in roughly 99% ofthe population, there is a 1:1 correlation between hemoglobinmeasurements and hematocrit levels. Thus, if hemoglobin test data isavailable, the hematocrit level is generally already known before startof the centrifuge-based sedimentation test.

Referring now to FIG. 18C, one embodiment of an assay protocol forhemoglobin-based hematocrit measurement will now be described. Blood wasdiluted 1:100 with water. The diluted sample was mixed (1:3) withmodified Drabkin's reagent (Sigma D5941, containing Contains sodiumbicarbonate, potassium ferricyanide, and potassium cyanide supplementedwith 0.015% Brij 35). After 10 minutes at 37 C, the absorbance of thereaction product (Cyan-met-hemoglobin) was measured at 540 nm. The assaywas calibrated with bovine hemoglobin (Sigma 2500) which gave a lineardose-response over the range 0-20 g/dL.

Using an assay protocol for hemoglobin-based measurement, correlation ofresults with hematocrit measurement will now be discussed. Human bloodsamples were processed by recombining plasma and red cells (collected bycentrifugation) to provide a wide range of hematocrit values. Thesesamples were assayed as above and by a standard centrifugal capillarytube hematocrit assay and results correlated as shown below. As seen inFIG. 18C, the resulting correlation was accurate with slope=1,intercept=zero and correlation coefficient (R^2)=0.99.

Another technique for hematocrit measurement involves microscopicimaging. Hematocrit can also be measured in the devices using a cuvettewith a fixed depth and a blood sample diluted to a known extent.Description of a system with such a cuvette can be found in U.S. patentapplication Ser. No. 13/244,947 fully incorporated herein by referencefor all purposes. Hematocrit can be determined by microscopicmeasurement of the (1) the red cell count per field of view and (2) theaverage red cell volume. Favored methods are: (1) Dark field microscopyand (2) (1)+Fluorescence microscopy using fluorescently-labeledanti-human CD-35 (red cell surface antigen). Image analysis techniquesare then applied.

Specifically, one method of measuring hematocrit may involve measuringoptical density of the sample. See for example Lipowsky et al.“Hematocrit determination in small bore tubes from optical densitymeasurements under white light illumination” Microvascular Research,Volume 20, Issue 1, July 1980, Pages 51-70;http://dx.doi.org/10.1016/0026-2862(80)90019-9, fully incorporatedherein by reference for all purposes. Lipowsky discusses therelationship between the hematocrit of blood flowing in small bore glasstubes and its optical density (OD) under white light (tungsten)illumination has been examined for various tube luminal diameters. In atleast some embodiments herein, all this data is available since asmall-bore tube of blood is being illuminated.

In another embodiment, hematocrit level can be determined by testing aportion of the blood sample under microscopy or other magnifiedobservation, such as but not limited to measuring the number and meansize of red blood cells in a defined observation area which may have aknown size. In this manner, the hematocrit may be determined based onsuch visual characterization of the red blood cells.

In yet another example, hematocrit level can be measured based on acompleted centrifugation of the blood sample which compacts the redblood cells. This compacted level can be used to determine hematocrit.In this example, only linear portions of the centrifuge basedsedimentation test are used to determine a corrected ESR. By way ofnon-limiting example, the first initial portion of interface positionmeasurement which is linear, along with the final end portion which isalso linear, are two portions of the sedimentation which may be used tocalculate an ESR corrected for hematocrit. As seen in FIG. 16, thisnon-limiting example may use a linear portion 182 of the sedimentationcurve corresponding to an initial period after centrifugation andanother linear portion 184 of the sedimentation curve near the end whencompaction is essentially complete curve is substantial flat. Thenon-linear portion of the sedimentation curve therebetween linearportions 182 and 184 are substantially not used to calculate thehematocrit correction factor.

The above is a non-exhaustive listing of hematocrit calculationtechniques and other methods of measuring hematocrit levels are notexcluded from use with the sedimentation measurement techniquesdescribed herein.

Graphs of Hematocrit Corrected ESR

FIG. 18B shows the logarithm of erythrocyte sedimentation ratesextracted from sedimentation profiles corrected for the effect ofhematocrit. As can be seen from the improvement in correlationcoefficient the hematocrit correction (for example, see FIG. 19A) iscapable of essentially eliminating the effects of hematocrit on ESR.

With hematocrit-adjusted clinical samples, good correlations with ESRwithin each hematocrit level, and, as expected, significant effects ofhematocrit were also found. The centrifugation method can also be usedto obtain accurate values for the hematocrit, and the impact ofhematocrit can be corrected.

FIG. 19, shows a re-plot of the data of FIG. 18B in which the effects ofhematocrit are clearly minimized as demonstrated by the good correlationof values of hematocrit-corrected ESR (present method) and ESR fromtraditional Westergren testing technique.

Referring now to FIG. 20, the relationship between thehematocrit-corrected ESR of the present method does not, however, have alinear relation to the Westergren ESR as seen in FIG. 19. To derive anestimate of the sedimentation rate that is linearly related to theWestergren ESR, the centrifuge-derived, hematocrit corrected data may befurther corrected using the formula:Estimated Westergren ESR=10^(((LOG(HCT correctedESR)−LOG(644.11))/0.1367)),where the relationship and parameters used are derived from the analysisof FIG. 18B.

FIG. 20 shows that the hematocrit-corrected and linearly-transformedLog(ESR) values obtained by the present embodiment as a function ofWestergren ESR (uncorrected for hematocrit). When the Log of theEstimated Westergren ESR from the centrifuge method was plotted againstthe log of the Westergren ESR as in FIG. 20, good correlation (R=0.90),slope (1.00) and intercept (0.00) values were obtained showingequivalence of the methods. Log values were plotted to show the fitacross the wide range of ESR values found (almost 100-fold).

Experimental Methods

The data obtained for the various charts were obtained using thefollowing techniques. These are provided as examples and are meant to benon-limiting.

Samples: Fresh EDTA-anticoagulated blood samples were used. EDTA is usedas this is the standard for the “Modified Westergren” method. Sampleswere kept at room temperature and re-suspended prior to measurement.

Hematocrit Adjustment: Samples were spun down for hematocrit packing(e.g. 5000 Relative centrifugal force (RCF) for 20 minutes), and plasmais separated from the cells. Red blood cells were slurried with plasmafrom the same sample and more plasma added to give a desired hematocritlevel.

Westergren ESR Measurements: A 1 mL sample is required to perform theWestergren ESR measurement (‘Sedigren’ brand tubes used, followingprotocol enclosed therein). Red blood cell sedimentation was observedand measured by video recording.

Adjustment of RBC Zeta Potential (and ESR) with Fibrinogen: For theexamples shown in FIGS. 11-14, bovine fibrinogen was dissolved in blood.In one example, a range of 0-10 mg/mL produced a range of 5-100 mm/h ESRfor a 40% hematocrit sample.

Measurement of Centrifuge Sedimentation Curve: A 25uL of whole bloodsample was added to a centrifuge vessel. A swinging bucket centrifuge asdescribed in co-pending U.S. patent applications Ser. Nos. 13/355,458and 13/244,947 were modified with a slot cut to allow light to passthrough the bucket when spinning in a horizontal fashion (axis ofrotation vertical). In this non-limiting example, the light source was 1W green LED, such as available from Thorlabs of Newton N.J., that isbrightness adjusted (typically ˜10%) so that light reaching the detectordid not saturate it. A webcam or other imaging device such as availablefrom Logitech was positioned at 10 mm above the plane of rotation asshown in FIG. 3. Integration time was 200 ms. Images were taken at 5frames/second (fps) using a loss-less compression codec (“huffyuv”) overknown times up to three minutes.

Image Transformation: images obtained visual observations of thecentrifuge vessels during centrifugation were processed in the manner asdescribed herein for FIGS. 6A to 7C.

Sedimentation curve extraction: the position over time of the red bloodcell/plasma and other interfaces in the images were then plotted in themanner as described herein for FIGS. 8A-9.

Curve Fitting With Hematocrit Correction Factor: The sedimentation curveis then further processed by way of curve fitting using varioustechniques described herein for FIGS. 10A-10B and FIG. 16-20, with orwithout Hematocrit correction factor(s), to derive sedimentation rateinformation.

Measurement of Non-Red Blood Cell Blood Components

Although the present description is written primarily in the context ofmeasuring erythrocyte sedimentation rate, it should be understood thatthe techniques herein can be adapted for use to measure sedimentationrates of other formed blood components that are not erythrocytes. Someembodiments may measure platelet sedimentation. Some embodiments maymeasure white blood cell sedimentation.

By way of nonlimiting example in FIG. 21, a kymograph obtained using thecentrifuge based methods as described herein also shows that in additionto the air/plasma interface 130 and erythrocyte/plasma interface 132,there is also a “shadow” showing a white blood cell and plasma interface141. Thus, both the red cell front red cell and a second sedimentationfront corresponding to white cells are observed in the sedimentationkymograph of FIG. 21.

Thus as seen in FIG. 21, some embodiments of the centrifugal method maybe used to sequentially or simultaneously measure white blood cellsedimentation rate which may be useful in characterizing certain aspectsof patient health. For example, white blood cells change their physicalcharacteristics when they are activated and/or aggregated. Bothphenomena are of great interest in evaluating white cell function. Whitecells sediment under centrifugal force, but they sediment at a rate moreslowly than red blood cells. The rate of white blood cell sedimentationis a function of at least one of the following: white blood celldensity, shape, and aggregation state. Measuring sedimentation rate canlead to detection of one or more these changes which may then be usedcharacterize certain aspects of patient health.

By way of nonlimiting example, it should be understood that the use ofchange in refractive index or possibly light scattering can be used as ameasure of the blood component interface position, rather than change inabsorbance. Optionally, some embodiments may use both. FIG. 21 showsdata indicating that the white blood cell interface is detectable due torefractive index or light scattering change rather than absorbancechange. In one embodiment, RBC interface position is based on absorbancechange due to the hemoglobin absorbing heavily in the green portion ofthe wavelength spectrum. RBC interface could perhaps be similarlymonitored if light of the right wavelength were used (very longwavelength). Thus, using light scattering or change in refractive indexcan also be used alone or in combination with absorbance as analternative way of measuring interface position or for detecting someinterface(s) such as for white blood cells or platelets that are notreadily visible by absorbance detection alone.

Assay Processing in an Integrated, Automated System

Referring now to FIG. 22, it should be understood that the processesdescribed herein may be performed using automated techniques. Theautomated processing may be used in an integrated, automated system. Insome embodiments, this may be in a single instrument having a pluralityof functional components therein and surrounded by a common housing. Theprocessing techniques and methods for sedimentation measure can bepre-set. Optionally, that may be based on protocols or procedures thatmay be dynamically changed as desired in the manner described in U.S.patent applications Ser. Nos. 13/355,458 and 13/244,947, both fullyincorporated herein by reference for all purposes.

In one non-limiting example as shown in FIG. 22, an integratedinstrument 500 may be provided with a programmable processor 502 whichcan be used to control a plurality of components of the instrument. Forexample, in one embodiment, the processor 502 may control a single ormultiple pipette system 504 that is movable X-Y and Z directions asindicated by arrows 506 and 508. The same or different processor mayalso control other components 512, 514, or 516 in the instrument. In oneembodiment, tone of the components 512, 514, or 516 comprises acentrifuge.

As seen in FIG. 22, control by the processor 502 may allow the pipettesystem 504 to acquire blood sample from cartridge 510 and move thesample to one of the components 512, 514, or 516. Such movement mayinvolve dispensing the sample into a removable vessel in the cartridge510 and then transporting the removable vessel to one of the components512, 514, or 516. Optionally, blood sample is dispensed directly into acontainer already mounted on one of the components 512, 514, or 516. Inone non-limiting example, one of these components 512, 514, or 516 maybe a centrifuge with an imaging configuration as shown in FIG. 3. Othercomponents 512, 514, or 516 perform other analysis, assay, or detectionfunctions.

All of the foregoing may be integrated within a single housing 520 andconfigured for bench top or small footprint floor mounting. In oneexample, a small footprint floor mounted system may occupy a floor areaof about 4 m² or less. In one example, a small footprint floor mountedsystem may occupy a floor area of about 3 m² or less. In one example, asmall footprint floor mounted system may occupy a floor area of about 2m² or less. In one example, a small footprint floor mounted system mayoccupy a floor area of about 1 m² or less. In some embodiments, theinstrument footprint may be less than or equal to about 4 m², 3 m², 2.5m², 2 m², 1.5 m², 1 m², 0.75 m², 0.5 m², 0.3 m², 0.2 m², 0.1 m², 0.08m², 0.05 m², 0.03 m², 100 cm², 80 cm², 70 cm², 60 cm², 50 cm², 40 cm²,30 cm², 20 cm², 15 cm², or 10 cm². Some suitable systems in apoint-of-service setting are described in U.S. patent applications Ser.Nos. 13/355,458 and 13/244,947, both fully incorporated herein byreference for all purposes. The present embodiments may be configuredfor use with any of the modules or systems described in those patentapplications.

While the invention has been described and illustrated with reference tocertain particular embodiments thereof, those skilled in the art willappreciate that various adaptations, changes, modifications,substitutions, deletions, or additions of procedures and protocols maybe made without departing from the spirit and scope of the invention.For example, with any of the above embodiments, it should be understoodthat other techniques for plasma separation may also be used with or inplace of centrifugation. For example, one embodiment may centrifuge thesample for an initial period, and then the sample may be located into afilter that then removes the formed blood components to completeseparation. Although the present embodiments are described in thecontext of centrifugation, other accelerated separation techniques mayalso be adapted for use with sedimentation rate measurement methodsdescribed herein. Some embodiments may optionally combine the hematocritcorrection techniques described herein with measurement techniques asdescribed in U.S. Pat. No. 6,204,066 fully incorporated herein byreference for all purposes. Some embodiments herein may pre-process theblood sample to pre-set the hematocrit value in the blood sample to apre-determined value so that the variable due to hematocrit is removed.Some embodiments may also use traditional techniques for adjusting forhematocrit levels. It should also be understood that although thepresent embodiments are described in the context of blood samples, thetechniques herein may also be configured to be applied to other samples(biological or otherwise).

Optionally, at least one embodiment may use a variable speed centrifuge.With feedback, such as but not limited to imaging of the position ofinterface(s) in the sample, the speed of the centrifuge could be variedto keep the compaction curve linear with time (until fully compacted),and the ESR data extracted from the speed profile of the centrifugerather than the sedimentation rate curve. In such a system, one or moreprocessors can be used to feedback control the centrifuge to have alinear compaction curve while speed profile of the centrifuge is alsorecorded. Depending on which interface is being tracked, thesedimentation rate data is calculated based centrifuge speed. In onenon-limiting example, a higher centrifuge speed is used to keep a linearcurve as the compaction nears completion.

Furthermore, those of skill in the art will recognize that any of theembodiments of the present invention can be applied to collection ofsample fluid from humans, animals, or other subjects. Optionally, thevolume of blood used for sedimentation testing may be 1 mL or less, 500μL or less, 300 μL or less, 250 μL or less, 200 μL or less, 170 μL orless, 150 μL or less, 125 μL or less, 100 μL or less, 75 μL or less, 50μL or less, 25 μL or less, 20 μL or less, 15 μL or less, 10 μL or less,5 μL or less, 3 μL or less, 1 μL or less, 500 nL or less, 250 nL orless, 100 nL or less, 50 nL or less, 20 nL or less, 10 nL or less, 5 nLor less, or 1 nL or less.

Additionally, concentrations, amounts, and other numerical data may bepresented herein in a range format. It is to be understood that suchrange format is used merely for convenience and brevity and should beinterpreted flexibly to include not only the numerical values explicitlyrecited as the limits of the range, but also to include all theindividual numerical values or sub-ranges encompassed within that rangeas if each numerical value and sub-range is explicitly recited. Forexample, a size range of about 1 nm to about 200 nm should beinterpreted to include not only the explicitly recited limits of about 1nm and about 200 nm, but also to include individual sizes such as 2 nm,3 nm, 4 nm, and sub-ranges such as 10 nm to 50 nm, 20 nm to 100 nm, etc.. . .

The publications discussed or cited herein are provided solely for theirdisclosure prior to the filing date of the present application. Nothingherein is to be construed as an admission that the present invention isnot entitled to antedate such publication by virtue of prior invention.Further, the dates of publication provided may be different from theactual publication dates which may need to be independently confirmed.All publications mentioned herein are incorporated herein by referenceto disclose and describe the structures and/or methods in connectionwith which the publications are cited. The following applications arefully incorporated herein by reference for all purposes: U.S. patentapplications Ser. Nos. 13/355,458 and 13/244,947.

Various aspects of at least some embodiments described herein areenumerated in the following paragraphs:

Aspect 1. A method comprising: using an accelerated blood componentseparation technique on a blood sample for a period of time to separateformed blood components from plasma; establishing a time-relatedcompaction curve for at least one formed blood component in said bloodsample after accelerated blood component separation has begun, saidcompaction curve having an initial approximately linear portion;determining sedimentation rate of the formed blood component based on atleast the following: the compaction curve and a hematocrit correctionfactor.

Aspect 2. A method comprising: centrifuging a blood sample in a vesselfor a period of time; establishing a time-related compaction curve forat least one formed blood component in said blood sample aftercentrifuging has begun, said compaction curve having an initialapproximately linear portion; correcting for hematocrit effect onsedimentation rate of the formed blood component by using a hematocritcorrection factor on the approximately linear portion of said compactioncurve.

Aspect 3. A method comprising: centrifuging a blood sample in a vesselfor a period of time; establishing a time-related compaction curve forat least one formed blood component in said blood sample aftercentrifuging has begun; correcting for impact of hematocrit onsedimentation rate of the formed blood component using a hematocritcorrection factor based on the formula:

${{U_{corr} = \frac{U_{uncorr}}{\left( {1 - \frac{\varphi}{\varphi_{\max}}} \right)^{\gamma}}},}\;$

where U_(uncorr) and U_(corr) are the uncorrected (raw) and correctedsedimentation rates, φ is the volume fraction of cells (hematocrit), andφ_(max) and γ are empirical parameters obtained by curve fitting

Aspect 4. The method of any one of the foregoing aspects, wherein curvefitting for the hematocrit correction factor comprises calibratingsedimentation rates from centrifuge based technique with sedimentationrates from a reference technique.

Aspect 5. The method of any one of the foregoing aspects, wherein thereference technique is the Westergren technique.

Aspect 6. The method of any one of the foregoing aspects, whereinfibrinogen levels as high as 15 mg/ml does not impact sedimentation ratemeasurement.

Aspect 7. The method of any one of the foregoing aspects, wherein saidblood sample is about 100 uL or less.

Aspect 8. The method of any one of the foregoing aspects, wherein saidblood sample is about 50 uL or less.

Aspect 9. The method of any one of the foregoing aspects, wherein saidblood sample is about 25 uL or less.

Aspect 10. The method of any one of the foregoing aspects, whereincentrifugation occurs at a first speed for a first period of time andthen at a second, faster speed for a second period of time.

Aspect 11. The method of any one of the foregoing aspects, whereincentrifugation uses a centrifuge configured to allow the blood sample tobe visually observed during centrifugation to establish interfacepositions of one or more formed blood components in the blood sample.

Aspect 12. The method of any one of the foregoing aspects, whereincentrifugation uses a centrifuge having a window thereon to enablevisual observation of the blood sample to establish erythrocyte/plasmainterface positions over time.

Aspect 13. The method of any one of the foregoing aspects, whereincentrifugation uses a centrifuge, a light source, and an image capturedevice to enable visual observation of the blood sample to establishformed blood component/plasma interface positions over time.

Aspect 14. The method of any one of the foregoing aspects, whereincompaction curve data is collected by capturing a plurality of images ofinterface positions of one or more formed blood components in thecentrifuge vessel over the time period.

Aspect 15. The method of aspect 14, wherein pixel positions in theplurality of images are used to accurately determine interface position.

Aspect 16. The method of aspect 14, wherein capturing of images beginsonce the centrifuge has reached a minimum operating speed.

Aspect 17. The method of aspect 14, wherein capturing of images beginswhen the centrifuge has begins rotation.

Aspect 18. The method of any one of the foregoing aspects, whereincompaction curve data is collected while the sample is beingcentrifuged.

Aspect 19. The method of any one of the foregoing aspects, whereincentrifugation is used to obtain accurate values for the hematocrit andto correct for hematocrit impact on sedimentation rate measurement.

Aspect 20. The method of any one of the foregoing aspects, whereincorrecting for hematocrit comprises calculating a mathematical functionfor a plurality of formed blood component interface positions occurringin said curve, said function being operative to correct forsedimentation rate variations due to hematocrit.

Aspect 21. The method of any one of the foregoing aspects, whereinhematocrit correction factor is determined without using data from anon-linear portion of the compaction curve.

Aspect 22. The method of any one of the foregoing aspects, whereinhematocrit level in the sample is derived from a technique separate fromcentrifugation.

Aspect 23. The method of any one of the foregoing aspects, whereinφ_(max) and γ are for fit optimization and do not relate directly tophysical parameters.

Aspect 24. The method of any one of the foregoing aspects, furthercomprising image transformation for conversion of a curved interface toa flat interface.

Aspect 25. The method of any one of the foregoing aspects, whereinhematocrit correction is capable of essentially eliminating the effectsof hematocrit on formed blood component sedimentation rate.

Aspect 26. The method of any one of the foregoing aspects, wherein imagetransformation parameters are selected, video of formed blood componentinterface position is put through image transformation, and then aregion of interest is chosen that covers both the whole range ofpositions for both air/plasma interface and erythrocyte interface.

Aspect 27. The method of any one of the foregoing aspects, wherein foreach timepoint in the video, pixel intensity values for each row acrossthe sample vessel within the region of interest are averaged to producea single column representing the intensity radially down the samplevessel.

Aspect 28. The method of any one of the foregoing aspects, whereincolumns for each timepoint are then assembled into a kymograph.

Aspect 29. The method of aspect 28 wherein positions of the two localmaxima of the image, one representing the air/plasma interface and otherthe plasma/erythrocyte interface are determined.

Aspect 30. The method of aspect 28 comprising converting pixel positionsinto volume occupied by the whole sample and volume occupied by redblood cells, wherein the y-position of the top and bottom of thecentrifuge vessel are used as reference locations together withknowledge of the shape of the centrifuge vessel.

Aspect 31. The method of any one of the foregoing aspects comprisingconverting plasma/erythrocyte interface position to the volume fractionoccupied by red blood cells and plotted against time as a centrifugesedimentation curve.

Aspect 32. The method of any one of the foregoing aspects, wherein alinear region of a sedimentation profile is used to extract asedimentation rate.

Aspect 33. The method of any one of the foregoing aspects, furthercomprising deriving an estimate of the sedimentation rate linearlyrelated to the Westergren ESR, the centrifuge-derived, hematocritcorrected data further corrected using the formula:Estimated Westergren ESR=10^(((LOG(HCT corrected ESR)−LOG(a))/b)).

Aspect 34. The method of any one of the foregoing aspects, furthercomprising hematocrit-correcting and linearly-transforming Log(ESR)values to establish a linear graph of sedimentation rate.

Aspect 35. The method of any one of the foregoing aspects wherein theblood sample is whole blood.

Aspect 36. The method of any one of the foregoing aspects wherein theblood sample is an anti-coagulated sample.

Aspect 37. The method of any one of the foregoing aspects wherein theformed blood component is white blood cells.

Aspect 38. The method of any one of the foregoing aspects wherein theformed blood component is platelets.

Aspect 39. The method of any one of the foregoing aspects, furthercomprising determining white cell sedimentation rate aftercentrifugation has begun, wherein measuring white cell sedimentationrate characterizes at least one of the following regarding the whiteblood cells: cell density, shape, and aggregation state.

Aspect 40. A method comprising: collecting a plurality of images offormed blood component and plasma interface positions over time from anaccelerated blood sample compaction process; performing imagetransformation on said plurality of images to transform images withcurved interfaces into corrected images with straight line interfaces;establishing a time-related compaction curve based on interfacepositions in said corrected images, for at least one formed bloodcomponent in said blood sample.

Aspect 41. A method comprising: centrifuging a blood sample in a vesselfor a period of time; collecting a plurality of images of formed bloodcomponent and plasma interface positions over time; performing imagetransformation on said images to transform images with curved interfacesinto corrected images with straight line interfaces; establishing atime-related compaction curve based on interface positions in saidcorrected images, for at least one formed blood component in said bloodsample after centrifuging has begun.

Aspect 42. A method comprising: using a programmableprocessor-controlled system to transfer at least a portion of a bloodsample from a blood sample location into a centrifugation vessel; usinga sample handling system under programmable processor control totransfer said vessel from a first addressable position to a centrifugewith a second addressable position; centrifuging the blood sample in thevessel for a period of time; collecting a plurality of images of formedblood component and plasma interface positions over time;

establishing a time-related compaction curve based on interfacepositions in said corrected images, for at least one formed bloodcomponent in said blood sample after centrifuging has begun.

Aspect 43. The method of any one of the foregoing aspects, wherein thecentrifuge has a rotor with a diameter of about 15 cm or less.

Aspect 44. The method of any one of the foregoing aspects, wherein thecentrifuge has a rotor with a diameter of about 10 cm or less.

Aspect 45. The method of any one of the foregoing aspects, wherein thecentrifuge has a rotor when in motion circumscribes an area with alongest dimension of about 15 cm or less.

Aspect 46. The method of any one of the foregoing aspects, wherein thecentrifuge has a rotor when in motion circumscribes an area with alongest dimension of about 10 cm or less.

Aspect 47. A method comprising: centrifuging a blood sample in a vesselfor a period of time; varying centrifuging speed to establishing alinear compaction curve of at least one formed blood component over theperiod of time until compacting has completed; monitoring centrifugingspeed profile for at least a portion of the time period; and determiningblood component sedimentation rate based on the centrifuging speedprofile.

Aspect 48. A method comprising: centrifuging a blood sample in a vesselfor a period of time; collecting at least a first single image of formedblood component and plasma interface positions at an initial time;collecting at least a second single image of formed blood component andplasma interface positions at a second time while rate of sedimentationis still linear; calculating sedimentation rate for at least one formedblood component in said blood sample based on linear sedimentation ratecalculated and a hematocrit correction factor.

Aspect 49. A device for use with a sample, the device comprising:

a centrifuge having a centrifuge vessel holder configured to allow fordetection of blood component interface position in the vessel holderduring centrifugation.

Aspect 50. The device of aspect 49, wherein the centrifuge has window toallow for visual observation of the centrifuge vessel holder duringcentrifugation.

Aspect 51. The device of aspect 49, wherein the centrifuge anillumination source to allow for detection of blood component interfaceposition in the sample.

Aspect 52. A system comprising: a centrifuge having a centrifuge vesselholder configured to allow for detection of blood component interfaceposition in the vessel holder in the vessel holder duringcentrifugation; a sample handling system for transporting a blood samplefrom a first location to a location on the centrifuge; and a processorprogrammed to record interface position during a least a portion ofcentrifugation.

While the above is a complete description of the various embodiments ofthe present invention, it is possible to use various alternatives,modifications and equivalents. Therefore, the scope of the presentinvention should be determined not with reference to the abovedescription but should, instead, be determined with reference to theappended claims, along with their full scope of equivalents. Anyfeature, whether preferred or not, may be combined with any otherfeature, whether preferred or not. The appended claims are not to beinterpreted as including means-plus-function limitations, unless such alimitation is explicitly recited in a given claim using the phrase“means for.” It should be understood that as used in the descriptionherein and throughout the claims that follow, the meaning of “a,” “an,”and “the” includes plural reference unless the context clearly dictatesotherwise. Also, as used in the description herein and throughout theclaims that follow, the meaning of “in” includes “in” and “on” unlessthe context clearly dictates otherwise. Finally, as used in thedescription herein and throughout the claims that follow, the meaningsof “and” and “or” include both the conjunctive and disjunctive and maybe used interchangeably unless the context expressly dictates otherwise.Thus, in contexts where the terms “and” or “or” are used, usage of suchconjunctions do not exclude an “and/or” meaning unless the contextexpressly dictates otherwise.

What is claimed is:
 1. A method comprising: using an accelerated bloodcomponent separation technique on a blood sample in a non-capillaryvessel for a first period of time at a first compaction force toseparate formed blood components from plasma, wherein the first periodof time occurs during an estimated linear portion of a compaction curve;using image capture of the sample at two different times during thefirst period of time to determine an uncorrected sedimentation ratebased on plasma/formed component interface location at those twodifferent times; using the accelerated blood component separationtechnique on the blood sample for a second period of time at a second,greater compaction force than the first compaction force; anddetermining sedimentation rate of the formed blood component based on atleast the following: the uncorrected sedimentation rate and a hematocritcorrection factor based on the hematocrit of the sample; wherein saiddetermining occurs without determining a mathematical function for anon-linear segment of the sedimentation curve representative of themagnitude of intercellular erythrocyte repulsion in the blood sample. 2.The method of claim 1 wherein the accelerated blood component separationtechnique comprises centrifuging the blood sample.
 3. The method ofclaim 2, wherein centrifugation occurs at a first speed for a firstperiod of time and then at a second, faster speed for a second period oftime.
 4. The method of claim 2, wherein centrifugation uses a centrifugeconfigured to allow the blood sample to be visually observed duringcentrifugation to establish interface positions of one or more formedblood components in the blood sample.
 5. The method of claim 2, whereincentrifugation uses a centrifuge having a window thereon to enablevisual observation of the blood sample to establish erythrocyte/plasmainterface positions over time.
 6. The method of claim 2, whereincentrifugation uses a centrifuge, a light source, and an image capturedevice to enable visual observation of the blood sample to establishformed blood component/plasma interface positions over time.
 7. Themethod of claim 2, wherein compaction curve data is collected bycapturing a plurality of images of interface positions of one or moreformed blood components in the centrifuge vessel over the time period.8. The method of claim 7, wherein pixel positions in the plurality ofimages are used to accurately determine interface position.
 9. Themethod of claim 7, wherein capturing of images begins once thecentrifuge has reached a minimum operating speed.
 10. The method ofclaim 7, wherein capturing of images begins when the centrifuge hasbegins rotation.
 11. The method of claim 1, wherein said blood sample isabout 100 uL or less.
 12. The method of claim 1, wherein said bloodsample is about 50 uL or less.
 13. The method of claim 1, whereincorrecting for hematocrit comprises calculating a mathematical functionfor a plurality of formed blood component interface positions occurringin said curve, said function being operative to correct forsedimentation rate variations due to hematocrit.
 14. The method of claim2, wherein compaction curve data is collected while the sample is beingcentrifuged.
 15. The method of claim 2, wherein centrifugation is usedto obtain accurate values for the hematocrit and to correct forhematocrit impact on sedimentation rate measurement.
 16. The method ofclaim 2, further comprising image transformation for conversion of acurved liquid interface to a flat interface.
 17. The method of claim 2,further comprising using a processor programmed to record interfaceposition during a least a portion of centrifugation.